The impact of social network structure on the growth and survival of online communities

2019 ◽  
Author(s):  
Sho Tsugawa ◽  
Sumaru Niida
Keyword(s):  
Social Network ◽  
Network Structure ◽  
Online Communities ◽  
Growth And Survival ◽  
Social Network Structure ◽  
The Impact

Online Communities and Social Network Structure

2019 ◽  
Author(s):  
Yanhao Wei ◽  
Wensi Zhang ◽  
Sha Yang ◽  
Xi Chen
Keyword(s):  
Social Network ◽  
Network Structure ◽  
Online Communities ◽  
Social Network Structure

scholarly journals Modelling the dispersion of SARS-CoV-2 on a dynamic network graph

2020 ◽  
Author(s):  
Patrick Bryant ◽  
Arne Elofsson
Keyword(s):  
Social Network ◽  
Network Structure ◽  
Preferential Attachment ◽  
Age Groups ◽  
Dynamic Network ◽  
Social Contacts ◽  
Social Network Structure ◽  
The Social ◽  
Epidemic Development ◽  
The Impact

AbstractBackgroundWhen modelling the dispersion of an epidemic using R0, one only considers the average number of individuals each infected individual will infect. However, we know from extensive studies of social networks that there is significant variation in the number of connections and thus social contacts each individual has. Individuals with more social contacts are more likely to attract and spread infection. These individuals are likely the drivers of the epidemic, so-called superspreaders. When many superspreaders are immune, it becomes more difficult for the disease to spread, as the connectedness of the social network dramatically decreases. If one assumes all individuals being equally connected and thus as likely to spread disease as in a SIR model, this is not true.MethodsTo account for the impact of social network structure on epidemic development, we model the dispersion of SARS-CoV-2 on a dynamic preferential attachment graph which changes appearance proportional to observed mobility changes. We sample a serial interval distribution that determines the probability of dispersion for all infected nodes each day. We model the dispersion in different age groups using age-specific infection fatality rates. We vary the infection probabilities in different age groups and analyse the outcome.ResultsThe impact of movement on network dynamics plays a crucial role in the spread of infections. We find that higher movement results in higher spread due to an increased probability of new connections being made within a social network. We show that saturation in the dispersion can be reached much earlier on a preferential attachment graph compared to spread on a random graph, which is more similar to estimations using R0.ConclusionsWe provide a novel method for modelling epidemics by using a dynamic network structure related to observed mobility changes. The social network structure plays a crucial role in epidemic development, something that is often overlooked.

scholarly journals Analysis of the Structural Characteristics of the Online Social Network of Chinese Professional Athletes

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yue Wang ◽  
Qian Huang ◽  
Qiurong Wang ◽  
Yang Xun ◽  
Yujiao Tan ◽  
...  
Keyword(s):  
Social Network ◽  
Network Structure ◽  
Structural Characteristics ◽  
Online Social Network ◽  
Support Network ◽  
Online Support ◽  
Physical And Mental Health ◽  
Social Network Structure ◽  
Relationship Structure ◽  
The Impact

In response to the lack of research on the online social network structure of athletes, elements of research on the online social network structure of athletes were constructed based on the whole network perspective and through the study of the characteristics of the whole online social network structure of athletes, in order to provide reference for the physical and mental health development of athletes from a new perspective. Data were collected through questionnaires, and several software programs were used to preprocess and analyse the collected data. Through the analysis of the online whole network structure, it was found that the network density of the online support network was generally greater than that of the online discussion network, and athletes still showed stronger practical support demands and behaved more rationally in the process of training and learning life, while from the perspective of the relationship structure, the athletes’ family and classmates’ online support is weaker than that in previous studies; in terms of the whole network, strong relationships still dominate in this population, while attention should be paid to the impact of weak relationships.

scholarly journals Assessing the Roles of Network Structure and Social Media in Inter-units Knowledge Sharing

2019 ◽  
Vol 2 (02) ◽  
pp. 95
Author(s):  
Djoko Sigit Sayogo ◽  
Sri Budi Cantika Yuli ◽  
Muhammad Sri Wahyudi Suliswanto ◽  
Wildan Affan
Keyword(s):  
Social Media ◽  
Quality Assurance ◽  
Social Network ◽  
Knowledge Sharing ◽  
Network Structure ◽  
Electronic Document ◽  
Social Network Structure ◽  
Quality Assurance Process ◽  
Assurance Process ◽  
The Impact

Sharing knowledge across different units within an organization can be considered as one of the organization’s fundamental operation. Nonetheless, sharing information and knowledge across boundaries presents tremendous challenges for organization. This paper discusses the impact of social network structure and social media in mediating knowledge sharing against unit task performance. Based on the review of extant literatures in intra-organization information and knowlegde sharing, this paper accentuates on three propositions as follows: a) the use of online collaborative media reduces time spend on task by accelerating the electronic document quality assurance process, b) integrating expert ability with the use of collaborative media reduces time spend on task by accelerating the electronic document quality assurance process, and c) social network structure increase the likelihood to extract personal advice from colleagues, thus improve unit’s work quality.

Evolutionary dynamics modeling of symbolic social network structure equilibrium

2020 ◽  
Vol 17 (10) ◽  
pp. 229-240
Author(s):  
Weijin Jiang ◽  
Sijian Lv ◽  
Yirong Jiang ◽  
Jiahui Chen ◽  
Fang Ye ◽  
...  
Keyword(s):  
Social Network ◽  
Network Structure ◽  
Evolutionary Dynamics ◽  
Dynamics Modeling ◽  
Social Network Structure

scholarly journals Inequality is rising where social network segregation interacts with urban topology

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Gergő Tóth ◽  
Johannes Wachs ◽  
Riccardo Di Clemente ◽  
Ákos Jakobi ◽  
Bence Ságvári ◽  
...  
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Network Structure ◽  
Urban Geography ◽  
Online Social Network ◽  
Stage Model ◽  
Significant Relationships ◽  
Social Segregation ◽  
Social Network Structure ◽  
Physical Barriers

AbstractSocial networks amplify inequalities by fundamental mechanisms of social tie formation such as homophily and triadic closure. These forces sharpen social segregation, which is reflected in fragmented social network structure. Geographical impediments such as distance and physical or administrative boundaries also reinforce social segregation. Yet, less is known about the joint relationships between social network structure, urban geography, and inequality. In this paper we analyze an online social network and find that the fragmentation of social networks is significantly higher in towns in which residential neighborhoods are divided by physical barriers such as rivers and railroads. Towns in which neighborhoods are relatively distant from the center of town and amenities are spatially concentrated are also more socially segregated. Using a two-stage model, we show that these urban geography features have significant relationships with income inequality via social network fragmentation. In other words, the geographic features of a place can compound economic inequalities via social networks.

Sign in / Sign up

Export Citation Format

Share Document